{"id":"https://openalex.org/W4414359856","doi":"https://doi.org/10.24963/ijcai.2025/734","title":"General Incomplete Time Series Analysis via Patch Dropping Without Imputation","display_name":"General Incomplete Time Series Analysis via Patch Dropping Without Imputation","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359856","doi":"https://doi.org/10.24963/ijcai.2025/734"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/734","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101976531","display_name":"Yangyang Wu","orcid":"https://orcid.org/0000-0001-9531-0906"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangyang Wu","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078503953","display_name":"Yang Yuan","orcid":"https://orcid.org/0000-0002-9698-5451"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yuan","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101547334","display_name":"Mengying Zhu","orcid":"https://orcid.org/0000-0002-9343-5729"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengying Zhu","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014150958","display_name":"Xiaoye Miao","orcid":"https://orcid.org/0000-0002-8632-1539"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoye Miao","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068256578","display_name":"Xi Meng","orcid":"https://orcid.org/0000-0002-7395-9269"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Xi","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101976531"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33412061,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6597","last_page":"6605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.875,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.875,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8309000134468079,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8134999871253967,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.7477999925613403},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7049000263214111},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6583999991416931},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6319000124931335},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6144999861717224}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7477999925613403},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7049000263214111},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6583999991416931},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6319000124931335},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6144999861717224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6046000123023987},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4129999876022339},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38670000433921814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3813000023365021},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3037000000476837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28870001435279846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/734","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Missing":[0],"values":[1],"in":[2,113],"multivariate":[3,16,58],"time":[4,17,59,76,86,117,132,150],"series":[5,18,60,77,87,133,151],"data":[6],"present":[7],"significant":[8],"challenges":[9],"to":[10,40,70,101,109,140,162],"effective":[11],"analysis.":[12],"Existing":[13],"methods":[14],"for":[15,56,131],"analysis":[19],"either":[20],"ignore":[21],"missing":[22],"data,":[23],"sacrificing":[24],"performance,":[25],"or":[26],"follow":[27],"the":[28,72,84,92,107,114,124,135],"impute-then-analyze":[29],"paradigm,":[30],"which":[31,62,98],"suffers":[32],"from":[33],"redundant":[34],"training":[35],"and":[36,43,91,106],"error":[37],"accumulation,":[38],"leading":[39],"biased":[41],"results":[42],"suboptimal":[44],"performance.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,99,120],"propose":[50,100],"INTER,":[51],"a":[52],"novel":[53,82],"end-to-end":[54],"framework":[55],"incomplete":[57,75,116],"analysis,":[61],"bypasses":[63],"imputation":[64],"by":[65,158],"leveraging":[66],"pre-trained":[67],"language":[68],"models":[69],"learn":[71],"distribution":[73],"of":[74,97],"data.":[78],"INTER":[79,155],"incorporates":[80],"two":[81],"components:":[83],"missing-rate-aware":[85],"patch-dropping":[88],"(MPD)":[89],"strategy":[90,126],"missing-aware":[93],"Transformer":[94],"block,":[95],"both":[96],"enhance":[102],"model":[103],"generalization,":[104],"robustness,":[105],"ability":[108],"capture":[110],"underlying":[111],"patterns":[112],"observed":[115],"series.":[118],"Moreover,":[119],"theoretically":[121],"prove":[122],"that":[123,154],"MPD":[125],"exhibits":[127],"lower":[128],"sample":[129],"variance":[130],"with":[134],"same":[136],"dropout":[137],"rate":[138],"compared":[139,161],"other":[141],"dropping":[142],"strategies.":[143],"Extensive":[144],"experiments":[145],"on":[146],"11":[147],"public":[148],"real-world":[149],"datasets":[152],"demonstrate":[153],"improves":[156],"accuracy":[157],"over":[159],"20%":[160],"state-of-the-art":[163],"methods,":[164],"while":[165],"maintaining":[166],"competitive":[167],"computational":[168],"efficiency.":[169]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
